1. The Fundamental Shift to RegTech and Data-Driven Finance (TechFin)
Ross P Buckley KPMG Law – KWM Professor of Disruptive Innovation, UNSW Sydney

2. Overview
Organising idea – The entity that knows the most about you is best placed to price credit or insurance for you. Traditionally that has been your bank.
Your bank did that by being embedded in the community – the local manager watched and heard things.
Increasingly banks have become data-driven businesses.
So it has been decades since mortgage decisions were made locally.
But now other companies know more about you – principally the big data and platform companies – Google, Amazon, Facebook, Apple, etc.
Banks need to become far more nimble with data, or face being usurped.
In this sense mandating open banking (over their objections) may save the banks lives.

3. Client Relationship (Fin)
Big Data (Tech)
Client Relationship (Fin)
Financial Services

4. TechFin – Stage One
TechFins provide much of the data – either raw or analysed – that banks and insurers use.

5. Financial institution
TechFin - Stage Two
TechFin
“Customers”
Conduit
Financial institution

6. Knowing your preferences from multiple sources…
Website / data: google (interest preferences), facebook (social media preferences) etc
Shopping: amazon, woolworths/coles frequent shopper (shopping preferences)
Phone: m-pesa (communication preferences)
Payment: alipay, visa/mastercard (shopping, travel preferences)
Allows Algorithms to know so much about you.
Data analytics rules!
Walmart – choker chain for dog, or stopper for a door. Multiply these correlations by tens of thousands!

7. The monetization of Data – The clear global trend, following China’s lead.
Money has been Digitized and Now Data is Monetized
FinTech Today
TechFin Tomorrow

8. China Influencing Business Decisions via Social Credit Scores
China's Social Credit System: AI-driven panopticon or fragmented foundation for a sincerity culture? – Masha Borak

9. Than 1% of the world’s data is analyzed,
Start
Than 1% of the world’s data is analyzed,
over 80% is unprotected
Source: Study: less than 1% of the world's data is analysed, over 80% is unprotected – J. Burn-Murdoch

10. When does a TechFin become a Financial Insitution?
Our thesis is that most TechFins will begin serving as a conduit connecting their customers with financial service providers
? : Conduit / front-end only? Data delivery & analytics?
Ant Financial <> Alibaba
Tencent <> WeBank
Google pay
Vodaone <> m-pesa
Large size, international / cross-border activity
Network fully developed
Enormous access to data
(+): money on balance sheet; discretion over client money; solicitation, pooling

11. TechFin – Stage Three
Stage Three, obviously, is TechFins providing financial services themselves, as is happening today on a major scale in China with Ant Financial.

12. TechFin Benefits
Reduction of transaction costs & enhanced market efficiency
Enhanced business decisions, risk management
Business decisions based on more comprehensive data set
Existing financial systems serve the credit needs of SMEs poorly
So better SME & consumer credit

13. TechFin Risks
TechFins have better data than traditional banks: more comprehensive front-end data, more data points, more reliable, cross-checked data
But: no level playing field with existing institutions, and a risk the triggers for existing regulation won’t be activated in time
Correlation vs Causation: False Predictions -- unkown effects of Artifical Intelligence / Data Analytics
Protected Factors at Risk? Upholding Civil Society Values (for instance, enforcing anti- racism, anti-gender discrimination etc)
Monopoly risks
Data protection risks – as we are seeing globaly
In countering these risks RegTech has a major role!

14. Should Regulators Care if TechFins Only Provide Data & Analytics?
If TechFins are essential to stability regulators should care.
If TechFin is essential for one or more important banks (eg main data analytics provider)
If TechFin moves to Stage 2 and is main front-end channel to customers, or if a TechFin serves this role for multiple providers.
Furthermore, if individuals are being harmed by analytics that produce damaging results, regulators should care.
So there is a strong case here for public regulation of TechFins. And RegTech will be essential in that task.

15. Theses
TechFins have their origin in BigData (“Tech”) rather than customer relationship (“Fin”).
For TechFins, formal financial regulation may be triggered too late. Triggers linked to taking deposits, soliciting customers or handling client funds are likely to not be triggered. Regulators may therefore be unable to a) enforce customer protection measures and b) monitor and mitigate systemic risk.
TechFins may compete unfairly therefore since they a) are unrestricted by risk & compliance considerations in their build-up phase, b) do not bear compliance and capital costs.
TechFins’ data analytics will require regulation at some stage. Perhaps “follow the data” will have to replace financial law’s “follow the money”.
Regulation of TechFin for now should focus on: a) information gathering, b) review of algorithms for false predictions and protected factors, and c) systemic risk prevention.

16. The Full Paper…
Dirk A. Zetzsche, Ross P. Buckley, Douglas W. Arner & Janos N Barberis “From FinTech to TechFin: The Regulatory Challenges of Data-Driven Finance,” forthcoming New York University Journal of Law and Business, See also: On the evolution of FinTech: On the transformative potential of RegTech: On the distributed liability of distributed ledgers: On Initial Coin Offerings:

17. Thank you.
Ross Buckley